Please use this identifier to cite or link to this item:
http://hdl.handle.net/10773/10913
Title: | Feature extraction and classification of biosignals: emotion valence detection from EEG Signals |
Author: | Tomé, A. M. Hidalgo-Muñoz, A. R. López, M. M. Teixeira, A. R. Santos, I. M. Pereira, A. T. Vázquez-Marrufo, M. Lang, E. W. |
Keywords: | Valence Detection Random Forest ERD/ERS |
Issue Date: | Feb-2013 |
Publisher: | SCITEPRESS |
Abstract: | In this work a valence recognition system based on electroencephalograms is presented. The performance of the system is evaluated for two settings: single subjects (intra-subject) and between subjects (inter-subject). The feature extraction is based on measures of relative energies computed in short time intervals and certain frequency bands. The feature extraction is performed either on signals averaged over an ensemble of trials or on single-trial response signals. The subsequent classification stage is based on an ensemble classifier, i. e. a random forest of tree classifiers. The classification is performed considering the ensemble average responses of all subjects (inter-subject) or considering the single-trial responses of single subjects (intra-subject). Applying a proper importance measure of the classifier, feature elimination has been used to identify the most relevant features of the decision making. |
Peer review: | yes |
URI: | http://hdl.handle.net/10773/10913 |
DOI: | 10.5220/0004233100540060 |
ISBN: | 978-989-8565-36-5 |
Appears in Collections: | IEETA - Comunicações |
Files in This Item:
File | Description | Size | Format | |
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BIOSIGNALS_2013_50_CR.pdf | 146.24 kB | Adobe PDF |
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